We don’t start with AI.
We start by watching how your business actually runs. The AI and automation come in only where it pays.
The work nobody documented
Every operation runs on a layer of undocumented workflow — the same record retyped into three systems, the report rebuilt every Monday that already exists somewhere else, the handoff that only works because one person remembers it. Nobody planned this; it accumulated one workaround at a time as tools got added and never got connected. And you can’t automate what you haven’t mapped, which is why “let’s use AI” stalls: the pilot gets built on an assumption about the workflow, the assumption is wrong, and the tool joins the pile of software your team routes around.
Three steps, in order — because skipping one is why most AI pilots don’t survive contact with the work.
Map
We sit with every person whose work touches the process and build a workflow register — each task, how often, how long, what breaks. Not a survey. Observation.
Triage
Every workflow gets scored on volume, cost, and how hard it is to automate given the systems you’re locked into. You get a ranked shortlist with dollars attached, and an honest list of what we recommend leaving alone.
Build & measure
We build one or two workflows first and measure them against the baseline before anything else rolls out. If the numbers don’t hold, we say so.
You own the output at every stage. If you stop after step one, you still have a document worth more than the fee.
Scoped to the process, not the company.
Operations Diagnostic
Workflow registers for every role in scope, an automation triage scored on cost and feasibility, and a ranked build plan with ROI ranges. Yours to keep, whether or not you work with us again.
Pilot Build
One or two workflows from the diagnostic, built, deployed, and measured against baseline. Scoped so you can judge the result before committing to more.
Managed Intelligence
Ongoing operation of what we build — monitoring, upkeep, and adjustment as your systems change. Priced against how much attention each workflow actually needs, not a flat rate that averages the easy ones with the hard ones.
Diagnostics are fixed-fee and scoped to the process, not the company. Ask and we’ll size it in one conversation.
Founded by a former Microsoft Senior Director from the Office of Applied Research — the group that takes AI from research into products people actually use.
From a recent engagement: a multi-location insurance agency. Discovery surfaced that customer-facing staff could not identify who had last worked an account roughly 70% of the time — a gap nobody in the business had named, in a market where a single point of retention is worth six figures. That finding came from sitting with one person for an hour. It reordered the entire build plan.
| Task | Freq. | Owner |
|---|---|---|
| Renewal follow-up | Daily | Rotates |
| Account handoff note | Per touch | Undocumented |
| Last touched by: unknown — ~70% of accounts | ||
“I genuinely can’t tell you who spoke to this customer last.” — frontline staff, discovery interview
QuantizedIQ was founded by Morris Kabuage, most recently a Senior Director in Microsoft’s Office of Applied Research — the group that moves AI from research into products people actually use. The work spanned Office, Windows, Teams, and SharePoint, and mostly came down to the unglamorous part: understanding how people really used a product before deciding what the model should do.
Twenty years in the Microsoft ecosystem preceded that: first as a program manager on SQL Server, building the product; then in the field organization as a business analyst, watching how the business actually bought and used it. Three vantage points on the same question — what happens in the gap between what technology can do and what an organization does with it.
QuantizedIQ is that gap, worked deliberately. Watch the work first. Build second.
Based in Newcastle, Washington, working across the Puget Sound region and remotely.
We already pay for software that’s supposed to do this.
Usually true, and usually part of the problem. The diagnostic often finds capability you’re already licensed for and nobody turned on. We’ll tell you that before we quote you anything new.
Is our data safe?
We design around your constraints, including vendor agreements that limit where your data can go. Where a workflow can run on infrastructure you own, we’ll build it that way.
How long before we see anything?
The diagnostic ends with a document you can act on. The first pilot ships after that, and it’s measured — you’ll know whether it worked, not just whether it’s live.
What if the answer is that we don’t need AI?
Then we say so and you keep the map. That’s happened, and it’s a better outcome than an automation nobody uses.
Start with the map.
A fixed-fee Operations Diagnostic — scoped to one process, no retainer, no commitment past the deliverable.